Timestamp for saved files: 2020-11-25_15-52-21
Training parameters
Number of epochs: 200
Step size maximum: 0.02
Step size decay: 9.9995e-05
Batch size: 64
Regularization rate: 0.0001
Saving validation predictions in: /Usersß/Josh Ehrlich/Courses/CISC881/Project/data\PredictionsValidation
Saving models in: /Usersß/Josh Ehrlich/Courses/CISC881/Project/data\SavedModels
*** Leave-one-out round # 0
Training on 5803 images, validating on 1515 images...
Model: "functional_1"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) [(None, 128, 128, 1) 0
__________________________________________________________________________________________________
conv2d (Conv2D) (None, 64, 64, 17) 170 input_1[0][0]
__________________________________________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 64, 64, 17) 0 conv2d[0][0]
__________________________________________________________________________________________________
conv2d_1 (Conv2D) (None, 32, 32, 32) 4928 max_pooling2d[0][0]
__________________________________________________________________________________________________
max_pooling2d_1 (MaxPooling2D) (None, 32, 32, 32) 0 conv2d_1[0][0]
__________________________________________________________________________________________________
conv2d_2 (Conv2D) (None, 16, 16, 47) 13583 max_pooling2d_1[0][0]
__________________________________________________________________________________________________
max_pooling2d_2 (MaxPooling2D) (None, 16, 16, 47) 0 conv2d_2[0][0]
__________________________________________________________________________________________________
conv2d_3 (Conv2D) (None, 8, 8, 62) 26288 max_pooling2d_2[0][0]
__________________________________________________________________________________________________
max_pooling2d_3 (MaxPooling2D) (None, 8, 8, 62) 0 conv2d_3[0][0]
__________________________________________________________________________________________________
conv2d_4 (Conv2D) (None, 4, 4, 77) 43043 max_pooling2d_3[0][0]
__________________________________________________________________________________________________
max_pooling2d_4 (MaxPooling2D) (None, 4, 4, 77) 0 conv2d_4[0][0]
__________________________________________________________________________________________________
conv2d_5 (Conv2D) (None, 2, 2, 92) 63848 max_pooling2d_4[0][0]
__________________________________________________________________________________________________
max_pooling2d_5 (MaxPooling2D) (None, 2, 2, 92) 0 conv2d_5[0][0]
__________________________________________________________________________________________________
conv2d_6 (Conv2D) (None, 1, 1, 107) 88703 max_pooling2d_5[0][0]
__________________________________________________________________________________________________
max_pooling2d_6 (MaxPooling2D) (None, 1, 1, 107) 0 conv2d_6[0][0]
__________________________________________________________________________________________________
up_sampling2d (UpSampling2D) (None, 2, 2, 107) 0 max_pooling2d_6[0][0]
__________________________________________________________________________________________________
concatenate (Concatenate) (None, 2, 2, 199) 0 up_sampling2d[0][0]
max_pooling2d_5[0][0]
__________________________________________________________________________________________________
conv2d_7 (Conv2D) (None, 2, 2, 92) 293020 concatenate[0][0]
__________________________________________________________________________________________________
batch_normalization (BatchNorma (None, 2, 2, 92) 368 conv2d_7[0][0]
__________________________________________________________________________________________________
up_sampling2d_1 (UpSampling2D) (None, 4, 4, 92) 0 batch_normalization[0][0]
__________________________________________________________________________________________________
concatenate_1 (Concatenate) (None, 4, 4, 169) 0 up_sampling2d_1[0][0]
max_pooling2d_4[0][0]
__________________________________________________________________________________________________
conv2d_8 (Conv2D) (None, 4, 4, 77) 208285 concatenate_1[0][0]
__________________________________________________________________________________________________
batch_normalization_1 (BatchNor (None, 4, 4, 77) 308 conv2d_8[0][0]
__________________________________________________________________________________________________
up_sampling2d_2 (UpSampling2D) (None, 8, 8, 77) 0 batch_normalization_1[0][0]
__________________________________________________________________________________________________
concatenate_2 (Concatenate) (None, 8, 8, 139) 0 up_sampling2d_2[0][0]
max_pooling2d_3[0][0]
__________________________________________________________________________________________________
conv2d_9 (Conv2D) (None, 8, 8, 62) 137950 concatenate_2[0][0]
__________________________________________________________________________________________________
batch_normalization_2 (BatchNor (None, 8, 8, 62) 248 conv2d_9[0][0]
__________________________________________________________________________________________________
up_sampling2d_3 (UpSampling2D) (None, 16, 16, 62) 0 batch_normalization_2[0][0]
__________________________________________________________________________________________________
concatenate_3 (Concatenate) (None, 16, 16, 109) 0 up_sampling2d_3[0][0]
max_pooling2d_2[0][0]
__________________________________________________________________________________________________
conv2d_10 (Conv2D) (None, 16, 16, 47) 82015 concatenate_3[0][0]
__________________________________________________________________________________________________
batch_normalization_3 (BatchNor (None, 16, 16, 47) 188 conv2d_10[0][0]
__________________________________________________________________________________________________
up_sampling2d_4 (UpSampling2D) (None, 32, 32, 47) 0 batch_normalization_3[0][0]
__________________________________________________________________________________________________
concatenate_4 (Concatenate) (None, 32, 32, 79) 0 up_sampling2d_4[0][0]
max_pooling2d_1[0][0]
__________________________________________________________________________________________________
conv2d_11 (Conv2D) (None, 32, 32, 32) 40480 concatenate_4[0][0]
__________________________________________________________________________________________________
batch_normalization_4 (BatchNor (None, 32, 32, 32) 128 conv2d_11[0][0]
__________________________________________________________________________________________________
up_sampling2d_5 (UpSampling2D) (None, 64, 64, 32) 0 batch_normalization_4[0][0]
__________________________________________________________________________________________________
concatenate_5 (Concatenate) (None, 64, 64, 49) 0 up_sampling2d_5[0][0]
max_pooling2d[0][0]
__________________________________________________________________________________________________
conv2d_12 (Conv2D) (None, 64, 64, 17) 13345 concatenate_5[0][0]
__________________________________________________________________________________________________
batch_normalization_5 (BatchNor (None, 64, 64, 17) 68 conv2d_12[0][0]
__________________________________________________________________________________________________
up_sampling2d_6 (UpSampling2D) (None, 128, 128, 17) 0 batch_normalization_5[0][0]
__________________________________________________________________________________________________
concatenate_6 (Concatenate) (None, 128, 128, 18) 0 up_sampling2d_6[0][0]
input_1[0][0]
__________________________________________________________________________________________________
conv2d_13 (Conv2D) (None, 128, 128, 2) 578 concatenate_6[0][0]
==================================================================================================
Total params: 1,017,544
Trainable params: 1,016,890
Non-trainable params: 654
__________________________________________________________________________________________________
TRAINING LOG <ultrasound_batch_generator.UltrasoundSegmentationBatchGenerator object at 0x000002AC2B6C5370>
WARNING:tensorflow:From <ipython-input-7-639783e879e1>:175: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.
Instructions for updating:
Please use Model.fit, which supports generators.
Training time: 6:42:10.418664
(1515, 128, 128, 1)
Total round time: 6:42:23.878649
*** Leave-one-out round # 1
Training on 6290 images, validating on 1028 images...
Model: "functional_3"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_2 (InputLayer) [(None, 128, 128, 1) 0
__________________________________________________________________________________________________
conv2d_14 (Conv2D) (None, 64, 64, 17) 170 input_2[0][0]
__________________________________________________________________________________________________
max_pooling2d_7 (MaxPooling2D) (None, 64, 64, 17) 0 conv2d_14[0][0]
__________________________________________________________________________________________________
conv2d_15 (Conv2D) (None, 32, 32, 32) 4928 max_pooling2d_7[0][0]
__________________________________________________________________________________________________
max_pooling2d_8 (MaxPooling2D) (None, 32, 32, 32) 0 conv2d_15[0][0]
__________________________________________________________________________________________________
conv2d_16 (Conv2D) (None, 16, 16, 47) 13583 max_pooling2d_8[0][0]
__________________________________________________________________________________________________
max_pooling2d_9 (MaxPooling2D) (None, 16, 16, 47) 0 conv2d_16[0][0]
__________________________________________________________________________________________________
conv2d_17 (Conv2D) (None, 8, 8, 62) 26288 max_pooling2d_9[0][0]
__________________________________________________________________________________________________
max_pooling2d_10 (MaxPooling2D) (None, 8, 8, 62) 0 conv2d_17[0][0]
__________________________________________________________________________________________________
conv2d_18 (Conv2D) (None, 4, 4, 77) 43043 max_pooling2d_10[0][0]
__________________________________________________________________________________________________
max_pooling2d_11 (MaxPooling2D) (None, 4, 4, 77) 0 conv2d_18[0][0]
__________________________________________________________________________________________________
conv2d_19 (Conv2D) (None, 2, 2, 92) 63848 max_pooling2d_11[0][0]
__________________________________________________________________________________________________
max_pooling2d_12 (MaxPooling2D) (None, 2, 2, 92) 0 conv2d_19[0][0]
__________________________________________________________________________________________________
conv2d_20 (Conv2D) (None, 1, 1, 107) 88703 max_pooling2d_12[0][0]
__________________________________________________________________________________________________
max_pooling2d_13 (MaxPooling2D) (None, 1, 1, 107) 0 conv2d_20[0][0]
__________________________________________________________________________________________________
up_sampling2d_7 (UpSampling2D) (None, 2, 2, 107) 0 max_pooling2d_13[0][0]
__________________________________________________________________________________________________
concatenate_7 (Concatenate) (None, 2, 2, 199) 0 up_sampling2d_7[0][0]
max_pooling2d_12[0][0]
__________________________________________________________________________________________________
conv2d_21 (Conv2D) (None, 2, 2, 92) 293020 concatenate_7[0][0]
__________________________________________________________________________________________________
batch_normalization_6 (BatchNor (None, 2, 2, 92) 368 conv2d_21[0][0]
__________________________________________________________________________________________________
up_sampling2d_8 (UpSampling2D) (None, 4, 4, 92) 0 batch_normalization_6[0][0]
__________________________________________________________________________________________________
concatenate_8 (Concatenate) (None, 4, 4, 169) 0 up_sampling2d_8[0][0]
max_pooling2d_11[0][0]
__________________________________________________________________________________________________
conv2d_22 (Conv2D) (None, 4, 4, 77) 208285 concatenate_8[0][0]
__________________________________________________________________________________________________
batch_normalization_7 (BatchNor (None, 4, 4, 77) 308 conv2d_22[0][0]
__________________________________________________________________________________________________
up_sampling2d_9 (UpSampling2D) (None, 8, 8, 77) 0 batch_normalization_7[0][0]
__________________________________________________________________________________________________
concatenate_9 (Concatenate) (None, 8, 8, 139) 0 up_sampling2d_9[0][0]
max_pooling2d_10[0][0]
__________________________________________________________________________________________________
conv2d_23 (Conv2D) (None, 8, 8, 62) 137950 concatenate_9[0][0]
__________________________________________________________________________________________________
batch_normalization_8 (BatchNor (None, 8, 8, 62) 248 conv2d_23[0][0]
__________________________________________________________________________________________________
up_sampling2d_10 (UpSampling2D) (None, 16, 16, 62) 0 batch_normalization_8[0][0]
__________________________________________________________________________________________________
concatenate_10 (Concatenate) (None, 16, 16, 109) 0 up_sampling2d_10[0][0]
max_pooling2d_9[0][0]
__________________________________________________________________________________________________
conv2d_24 (Conv2D) (None, 16, 16, 47) 82015 concatenate_10[0][0]
__________________________________________________________________________________________________
batch_normalization_9 (BatchNor (None, 16, 16, 47) 188 conv2d_24[0][0]
__________________________________________________________________________________________________
up_sampling2d_11 (UpSampling2D) (None, 32, 32, 47) 0 batch_normalization_9[0][0]
__________________________________________________________________________________________________
concatenate_11 (Concatenate) (None, 32, 32, 79) 0 up_sampling2d_11[0][0]
max_pooling2d_8[0][0]
__________________________________________________________________________________________________
conv2d_25 (Conv2D) (None, 32, 32, 32) 40480 concatenate_11[0][0]
__________________________________________________________________________________________________
batch_normalization_10 (BatchNo (None, 32, 32, 32) 128 conv2d_25[0][0]
__________________________________________________________________________________________________
up_sampling2d_12 (UpSampling2D) (None, 64, 64, 32) 0 batch_normalization_10[0][0]
__________________________________________________________________________________________________
concatenate_12 (Concatenate) (None, 64, 64, 49) 0 up_sampling2d_12[0][0]
max_pooling2d_7[0][0]
__________________________________________________________________________________________________
conv2d_26 (Conv2D) (None, 64, 64, 17) 13345 concatenate_12[0][0]
__________________________________________________________________________________________________
batch_normalization_11 (BatchNo (None, 64, 64, 17) 68 conv2d_26[0][0]
__________________________________________________________________________________________________
up_sampling2d_13 (UpSampling2D) (None, 128, 128, 17) 0 batch_normalization_11[0][0]
__________________________________________________________________________________________________
concatenate_13 (Concatenate) (None, 128, 128, 18) 0 up_sampling2d_13[0][0]
input_2[0][0]
__________________________________________________________________________________________________
conv2d_27 (Conv2D) (None, 128, 128, 2) 578 concatenate_13[0][0]
==================================================================================================
Total params: 1,017,544
Trainable params: 1,016,890
Non-trainable params: 654
__________________________________________________________________________________________________
TRAINING LOG <ultrasound_batch_generator.UltrasoundSegmentationBatchGenerator object at 0x000002AC2DC35AC0>
Training time: 7:10:14.589074
(1028, 128, 128, 1)
Total round time: 7:10:23.704911
*** Leave-one-out round # 2
Training on 6670 images, validating on 648 images...
Model: "functional_5"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_3 (InputLayer) [(None, 128, 128, 1) 0
__________________________________________________________________________________________________
conv2d_28 (Conv2D) (None, 64, 64, 17) 170 input_3[0][0]
__________________________________________________________________________________________________
max_pooling2d_14 (MaxPooling2D) (None, 64, 64, 17) 0 conv2d_28[0][0]
__________________________________________________________________________________________________
conv2d_29 (Conv2D) (None, 32, 32, 32) 4928 max_pooling2d_14[0][0]
__________________________________________________________________________________________________
max_pooling2d_15 (MaxPooling2D) (None, 32, 32, 32) 0 conv2d_29[0][0]
__________________________________________________________________________________________________
conv2d_30 (Conv2D) (None, 16, 16, 47) 13583 max_pooling2d_15[0][0]
__________________________________________________________________________________________________
max_pooling2d_16 (MaxPooling2D) (None, 16, 16, 47) 0 conv2d_30[0][0]
__________________________________________________________________________________________________
conv2d_31 (Conv2D) (None, 8, 8, 62) 26288 max_pooling2d_16[0][0]
__________________________________________________________________________________________________
max_pooling2d_17 (MaxPooling2D) (None, 8, 8, 62) 0 conv2d_31[0][0]
__________________________________________________________________________________________________
conv2d_32 (Conv2D) (None, 4, 4, 77) 43043 max_pooling2d_17[0][0]
__________________________________________________________________________________________________
max_pooling2d_18 (MaxPooling2D) (None, 4, 4, 77) 0 conv2d_32[0][0]
__________________________________________________________________________________________________
conv2d_33 (Conv2D) (None, 2, 2, 92) 63848 max_pooling2d_18[0][0]
__________________________________________________________________________________________________
max_pooling2d_19 (MaxPooling2D) (None, 2, 2, 92) 0 conv2d_33[0][0]
__________________________________________________________________________________________________
conv2d_34 (Conv2D) (None, 1, 1, 107) 88703 max_pooling2d_19[0][0]
__________________________________________________________________________________________________
max_pooling2d_20 (MaxPooling2D) (None, 1, 1, 107) 0 conv2d_34[0][0]
__________________________________________________________________________________________________
up_sampling2d_14 (UpSampling2D) (None, 2, 2, 107) 0 max_pooling2d_20[0][0]
__________________________________________________________________________________________________
concatenate_14 (Concatenate) (None, 2, 2, 199) 0 up_sampling2d_14[0][0]
max_pooling2d_19[0][0]
__________________________________________________________________________________________________
conv2d_35 (Conv2D) (None, 2, 2, 92) 293020 concatenate_14[0][0]
__________________________________________________________________________________________________
batch_normalization_12 (BatchNo (None, 2, 2, 92) 368 conv2d_35[0][0]
__________________________________________________________________________________________________
up_sampling2d_15 (UpSampling2D) (None, 4, 4, 92) 0 batch_normalization_12[0][0]
__________________________________________________________________________________________________
concatenate_15 (Concatenate) (None, 4, 4, 169) 0 up_sampling2d_15[0][0]
max_pooling2d_18[0][0]
__________________________________________________________________________________________________
conv2d_36 (Conv2D) (None, 4, 4, 77) 208285 concatenate_15[0][0]
__________________________________________________________________________________________________
batch_normalization_13 (BatchNo (None, 4, 4, 77) 308 conv2d_36[0][0]
__________________________________________________________________________________________________
up_sampling2d_16 (UpSampling2D) (None, 8, 8, 77) 0 batch_normalization_13[0][0]
__________________________________________________________________________________________________
concatenate_16 (Concatenate) (None, 8, 8, 139) 0 up_sampling2d_16[0][0]
max_pooling2d_17[0][0]
__________________________________________________________________________________________________
conv2d_37 (Conv2D) (None, 8, 8, 62) 137950 concatenate_16[0][0]
__________________________________________________________________________________________________
batch_normalization_14 (BatchNo (None, 8, 8, 62) 248 conv2d_37[0][0]
__________________________________________________________________________________________________
up_sampling2d_17 (UpSampling2D) (None, 16, 16, 62) 0 batch_normalization_14[0][0]
__________________________________________________________________________________________________
concatenate_17 (Concatenate) (None, 16, 16, 109) 0 up_sampling2d_17[0][0]
max_pooling2d_16[0][0]
__________________________________________________________________________________________________
conv2d_38 (Conv2D) (None, 16, 16, 47) 82015 concatenate_17[0][0]
__________________________________________________________________________________________________
batch_normalization_15 (BatchNo (None, 16, 16, 47) 188 conv2d_38[0][0]
__________________________________________________________________________________________________
up_sampling2d_18 (UpSampling2D) (None, 32, 32, 47) 0 batch_normalization_15[0][0]
__________________________________________________________________________________________________
concatenate_18 (Concatenate) (None, 32, 32, 79) 0 up_sampling2d_18[0][0]
max_pooling2d_15[0][0]
__________________________________________________________________________________________________
conv2d_39 (Conv2D) (None, 32, 32, 32) 40480 concatenate_18[0][0]
__________________________________________________________________________________________________
batch_normalization_16 (BatchNo (None, 32, 32, 32) 128 conv2d_39[0][0]
__________________________________________________________________________________________________
up_sampling2d_19 (UpSampling2D) (None, 64, 64, 32) 0 batch_normalization_16[0][0]
__________________________________________________________________________________________________
concatenate_19 (Concatenate) (None, 64, 64, 49) 0 up_sampling2d_19[0][0]
max_pooling2d_14[0][0]
__________________________________________________________________________________________________
conv2d_40 (Conv2D) (None, 64, 64, 17) 13345 concatenate_19[0][0]
__________________________________________________________________________________________________
batch_normalization_17 (BatchNo (None, 64, 64, 17) 68 conv2d_40[0][0]
__________________________________________________________________________________________________
up_sampling2d_20 (UpSampling2D) (None, 128, 128, 17) 0 batch_normalization_17[0][0]
__________________________________________________________________________________________________
concatenate_20 (Concatenate) (None, 128, 128, 18) 0 up_sampling2d_20[0][0]
input_3[0][0]
__________________________________________________________________________________________________
conv2d_41 (Conv2D) (None, 128, 128, 2) 578 concatenate_20[0][0]
==================================================================================================
Total params: 1,017,544
Trainable params: 1,016,890
Non-trainable params: 654
__________________________________________________________________________________________________
TRAINING LOG <ultrasound_batch_generator.UltrasoundSegmentationBatchGenerator object at 0x000002AC34315F70>
Training time: 7:34:28.907510
(648, 128, 128, 1)
Total round time: 7:34:34.866427
*** Leave-one-out round # 3
Training on 6580 images, validating on 738 images...
Model: "functional_7"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_4 (InputLayer) [(None, 128, 128, 1) 0
__________________________________________________________________________________________________
conv2d_42 (Conv2D) (None, 64, 64, 17) 170 input_4[0][0]
__________________________________________________________________________________________________
max_pooling2d_21 (MaxPooling2D) (None, 64, 64, 17) 0 conv2d_42[0][0]
__________________________________________________________________________________________________
conv2d_43 (Conv2D) (None, 32, 32, 32) 4928 max_pooling2d_21[0][0]
__________________________________________________________________________________________________
max_pooling2d_22 (MaxPooling2D) (None, 32, 32, 32) 0 conv2d_43[0][0]
__________________________________________________________________________________________________
conv2d_44 (Conv2D) (None, 16, 16, 47) 13583 max_pooling2d_22[0][0]
__________________________________________________________________________________________________
max_pooling2d_23 (MaxPooling2D) (None, 16, 16, 47) 0 conv2d_44[0][0]
__________________________________________________________________________________________________
conv2d_45 (Conv2D) (None, 8, 8, 62) 26288 max_pooling2d_23[0][0]
__________________________________________________________________________________________________
max_pooling2d_24 (MaxPooling2D) (None, 8, 8, 62) 0 conv2d_45[0][0]
__________________________________________________________________________________________________
conv2d_46 (Conv2D) (None, 4, 4, 77) 43043 max_pooling2d_24[0][0]
__________________________________________________________________________________________________
max_pooling2d_25 (MaxPooling2D) (None, 4, 4, 77) 0 conv2d_46[0][0]
__________________________________________________________________________________________________
conv2d_47 (Conv2D) (None, 2, 2, 92) 63848 max_pooling2d_25[0][0]
__________________________________________________________________________________________________
max_pooling2d_26 (MaxPooling2D) (None, 2, 2, 92) 0 conv2d_47[0][0]
__________________________________________________________________________________________________
conv2d_48 (Conv2D) (None, 1, 1, 107) 88703 max_pooling2d_26[0][0]
__________________________________________________________________________________________________
max_pooling2d_27 (MaxPooling2D) (None, 1, 1, 107) 0 conv2d_48[0][0]
__________________________________________________________________________________________________
up_sampling2d_21 (UpSampling2D) (None, 2, 2, 107) 0 max_pooling2d_27[0][0]
__________________________________________________________________________________________________
concatenate_21 (Concatenate) (None, 2, 2, 199) 0 up_sampling2d_21[0][0]
max_pooling2d_26[0][0]
__________________________________________________________________________________________________
conv2d_49 (Conv2D) (None, 2, 2, 92) 293020 concatenate_21[0][0]
__________________________________________________________________________________________________
batch_normalization_18 (BatchNo (None, 2, 2, 92) 368 conv2d_49[0][0]
__________________________________________________________________________________________________
up_sampling2d_22 (UpSampling2D) (None, 4, 4, 92) 0 batch_normalization_18[0][0]
__________________________________________________________________________________________________
concatenate_22 (Concatenate) (None, 4, 4, 169) 0 up_sampling2d_22[0][0]
max_pooling2d_25[0][0]
__________________________________________________________________________________________________
conv2d_50 (Conv2D) (None, 4, 4, 77) 208285 concatenate_22[0][0]
__________________________________________________________________________________________________
batch_normalization_19 (BatchNo (None, 4, 4, 77) 308 conv2d_50[0][0]
__________________________________________________________________________________________________
up_sampling2d_23 (UpSampling2D) (None, 8, 8, 77) 0 batch_normalization_19[0][0]
__________________________________________________________________________________________________
concatenate_23 (Concatenate) (None, 8, 8, 139) 0 up_sampling2d_23[0][0]
max_pooling2d_24[0][0]
__________________________________________________________________________________________________
conv2d_51 (Conv2D) (None, 8, 8, 62) 137950 concatenate_23[0][0]
__________________________________________________________________________________________________
batch_normalization_20 (BatchNo (None, 8, 8, 62) 248 conv2d_51[0][0]
__________________________________________________________________________________________________
up_sampling2d_24 (UpSampling2D) (None, 16, 16, 62) 0 batch_normalization_20[0][0]
__________________________________________________________________________________________________
concatenate_24 (Concatenate) (None, 16, 16, 109) 0 up_sampling2d_24[0][0]
max_pooling2d_23[0][0]
__________________________________________________________________________________________________
conv2d_52 (Conv2D) (None, 16, 16, 47) 82015 concatenate_24[0][0]
__________________________________________________________________________________________________
batch_normalization_21 (BatchNo (None, 16, 16, 47) 188 conv2d_52[0][0]
__________________________________________________________________________________________________
up_sampling2d_25 (UpSampling2D) (None, 32, 32, 47) 0 batch_normalization_21[0][0]
__________________________________________________________________________________________________
concatenate_25 (Concatenate) (None, 32, 32, 79) 0 up_sampling2d_25[0][0]
max_pooling2d_22[0][0]
__________________________________________________________________________________________________
conv2d_53 (Conv2D) (None, 32, 32, 32) 40480 concatenate_25[0][0]
__________________________________________________________________________________________________
batch_normalization_22 (BatchNo (None, 32, 32, 32) 128 conv2d_53[0][0]
__________________________________________________________________________________________________
up_sampling2d_26 (UpSampling2D) (None, 64, 64, 32) 0 batch_normalization_22[0][0]
__________________________________________________________________________________________________
concatenate_26 (Concatenate) (None, 64, 64, 49) 0 up_sampling2d_26[0][0]
max_pooling2d_21[0][0]
__________________________________________________________________________________________________
conv2d_54 (Conv2D) (None, 64, 64, 17) 13345 concatenate_26[0][0]
__________________________________________________________________________________________________
batch_normalization_23 (BatchNo (None, 64, 64, 17) 68 conv2d_54[0][0]
__________________________________________________________________________________________________
up_sampling2d_27 (UpSampling2D) (None, 128, 128, 17) 0 batch_normalization_23[0][0]
__________________________________________________________________________________________________
concatenate_27 (Concatenate) (None, 128, 128, 18) 0 up_sampling2d_27[0][0]
input_4[0][0]
__________________________________________________________________________________________________
conv2d_55 (Conv2D) (None, 128, 128, 2) 578 concatenate_27[0][0]
==================================================================================================
Total params: 1,017,544
Trainable params: 1,016,890
Non-trainable params: 654
__________________________________________________________________________________________________
TRAINING LOG <ultrasound_batch_generator.UltrasoundSegmentationBatchGenerator object at 0x000002AC2D200400>
Training time: 7:27:11.132603
(738, 128, 128, 1)
Total round time: 7:27:17.788498
*** Leave-one-out round # 4
Training on 6689 images, validating on 629 images...
Model: "functional_9"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_5 (InputLayer) [(None, 128, 128, 1) 0
__________________________________________________________________________________________________
conv2d_56 (Conv2D) (None, 64, 64, 17) 170 input_5[0][0]
__________________________________________________________________________________________________
max_pooling2d_28 (MaxPooling2D) (None, 64, 64, 17) 0 conv2d_56[0][0]
__________________________________________________________________________________________________
conv2d_57 (Conv2D) (None, 32, 32, 32) 4928 max_pooling2d_28[0][0]
__________________________________________________________________________________________________
max_pooling2d_29 (MaxPooling2D) (None, 32, 32, 32) 0 conv2d_57[0][0]
__________________________________________________________________________________________________
conv2d_58 (Conv2D) (None, 16, 16, 47) 13583 max_pooling2d_29[0][0]
__________________________________________________________________________________________________
max_pooling2d_30 (MaxPooling2D) (None, 16, 16, 47) 0 conv2d_58[0][0]
__________________________________________________________________________________________________
conv2d_59 (Conv2D) (None, 8, 8, 62) 26288 max_pooling2d_30[0][0]
__________________________________________________________________________________________________
max_pooling2d_31 (MaxPooling2D) (None, 8, 8, 62) 0 conv2d_59[0][0]
__________________________________________________________________________________________________
conv2d_60 (Conv2D) (None, 4, 4, 77) 43043 max_pooling2d_31[0][0]
__________________________________________________________________________________________________
max_pooling2d_32 (MaxPooling2D) (None, 4, 4, 77) 0 conv2d_60[0][0]
__________________________________________________________________________________________________
conv2d_61 (Conv2D) (None, 2, 2, 92) 63848 max_pooling2d_32[0][0]
__________________________________________________________________________________________________
max_pooling2d_33 (MaxPooling2D) (None, 2, 2, 92) 0 conv2d_61[0][0]
__________________________________________________________________________________________________
conv2d_62 (Conv2D) (None, 1, 1, 107) 88703 max_pooling2d_33[0][0]
__________________________________________________________________________________________________
max_pooling2d_34 (MaxPooling2D) (None, 1, 1, 107) 0 conv2d_62[0][0]
__________________________________________________________________________________________________
up_sampling2d_28 (UpSampling2D) (None, 2, 2, 107) 0 max_pooling2d_34[0][0]
__________________________________________________________________________________________________
concatenate_28 (Concatenate) (None, 2, 2, 199) 0 up_sampling2d_28[0][0]
max_pooling2d_33[0][0]
__________________________________________________________________________________________________
conv2d_63 (Conv2D) (None, 2, 2, 92) 293020 concatenate_28[0][0]
__________________________________________________________________________________________________
batch_normalization_24 (BatchNo (None, 2, 2, 92) 368 conv2d_63[0][0]
__________________________________________________________________________________________________
up_sampling2d_29 (UpSampling2D) (None, 4, 4, 92) 0 batch_normalization_24[0][0]
__________________________________________________________________________________________________
concatenate_29 (Concatenate) (None, 4, 4, 169) 0 up_sampling2d_29[0][0]
max_pooling2d_32[0][0]
__________________________________________________________________________________________________
conv2d_64 (Conv2D) (None, 4, 4, 77) 208285 concatenate_29[0][0]
__________________________________________________________________________________________________
batch_normalization_25 (BatchNo (None, 4, 4, 77) 308 conv2d_64[0][0]
__________________________________________________________________________________________________
up_sampling2d_30 (UpSampling2D) (None, 8, 8, 77) 0 batch_normalization_25[0][0]
__________________________________________________________________________________________________
concatenate_30 (Concatenate) (None, 8, 8, 139) 0 up_sampling2d_30[0][0]
max_pooling2d_31[0][0]
__________________________________________________________________________________________________
conv2d_65 (Conv2D) (None, 8, 8, 62) 137950 concatenate_30[0][0]
__________________________________________________________________________________________________
batch_normalization_26 (BatchNo (None, 8, 8, 62) 248 conv2d_65[0][0]
__________________________________________________________________________________________________
up_sampling2d_31 (UpSampling2D) (None, 16, 16, 62) 0 batch_normalization_26[0][0]
__________________________________________________________________________________________________
concatenate_31 (Concatenate) (None, 16, 16, 109) 0 up_sampling2d_31[0][0]
max_pooling2d_30[0][0]
__________________________________________________________________________________________________
conv2d_66 (Conv2D) (None, 16, 16, 47) 82015 concatenate_31[0][0]
__________________________________________________________________________________________________
batch_normalization_27 (BatchNo (None, 16, 16, 47) 188 conv2d_66[0][0]
__________________________________________________________________________________________________
up_sampling2d_32 (UpSampling2D) (None, 32, 32, 47) 0 batch_normalization_27[0][0]
__________________________________________________________________________________________________
concatenate_32 (Concatenate) (None, 32, 32, 79) 0 up_sampling2d_32[0][0]
max_pooling2d_29[0][0]
__________________________________________________________________________________________________
conv2d_67 (Conv2D) (None, 32, 32, 32) 40480 concatenate_32[0][0]
__________________________________________________________________________________________________
batch_normalization_28 (BatchNo (None, 32, 32, 32) 128 conv2d_67[0][0]
__________________________________________________________________________________________________
up_sampling2d_33 (UpSampling2D) (None, 64, 64, 32) 0 batch_normalization_28[0][0]
__________________________________________________________________________________________________
concatenate_33 (Concatenate) (None, 64, 64, 49) 0 up_sampling2d_33[0][0]
max_pooling2d_28[0][0]
__________________________________________________________________________________________________
conv2d_68 (Conv2D) (None, 64, 64, 17) 13345 concatenate_33[0][0]
__________________________________________________________________________________________________
batch_normalization_29 (BatchNo (None, 64, 64, 17) 68 conv2d_68[0][0]
__________________________________________________________________________________________________
up_sampling2d_34 (UpSampling2D) (None, 128, 128, 17) 0 batch_normalization_29[0][0]
__________________________________________________________________________________________________
concatenate_34 (Concatenate) (None, 128, 128, 18) 0 up_sampling2d_34[0][0]
input_5[0][0]
__________________________________________________________________________________________________
conv2d_69 (Conv2D) (None, 128, 128, 2) 578 concatenate_34[0][0]
==================================================================================================
Total params: 1,017,544
Trainable params: 1,016,890
Non-trainable params: 654
__________________________________________________________________________________________________
TRAINING LOG <ultrasound_batch_generator.UltrasoundSegmentationBatchGenerator object at 0x000002AC2C9F2B20>
Training time: 7:33:34.531170
(629, 128, 128, 1)
Total round time: 7:33:40.234246
Total training time: 1 day, 12:28:56.308730